Summary

This resource emphasizes statistical inference and sound decision-making through its extensive coverage of data collection and analysis. As in earlier editions, it helps develop statistical thinking and promotes inference assessment- from the vantage point of both the consumer and the producer. Includes new Three-phased Examples that contain three components: "problem," "solution," and "look back." Provides Now Work exercises that follow each example, suggesting an end-of-section exercise that is similar in style and concept to the example. Offers new Chapter Summary Notes along with end-of- chapter material. Provides new Critical Thinking Challenges. A comprehensive resource for anyone who needs to improve their understanding of statistics.

Table of Contents

Statistics, Data, and Statistical Thinking

The Science of Statistics

Types of Statistical Applications

Fundamental Elements of Statistics

Types of Data

Collecting Data

The Role of Statistics in Critical Thinking

Methods for Describing Sets of Data

Describing Qualitative Data

Graphical Methods for Describing Quantitative Data

Summation Notation

Numerical Measures of Central Tendency

Numerical Measures of Variability

Interpreting the Standard Deviation

Numerical Measures of Relative Standing

Methods for Detecting Outliers (Optional)

Graphing Bivariate Relationships (Optional)

Distorting the Truth with Descriptive Techniques

Probability

Events, Sample Spaces, and Probability

Unions and Intersections

Complementary Events

The Additive Rule and Mutually Exclusive Events

Conditional Probability

The Multiplicative Rule and Independent Events

Random Sampling

Some Counting Rules (Optional)

Discrete Random Variables

Two Types of Random Variables

Probability Distributions for Discrete Random Variables

Expected Values of Discrete Random Variables

The Binomial Random Variable

The Poisson Random Variable (Optional)

The Hypergeometric Random Variable (Optional)

Continuous Random Variables

Continuous Probability Distributions

The Uniform Distribution

The Normal Distribution

Descriptive Methods for Assessing Normality

Approximating a Binomial Distribution with a Normal Distribution (Optional)

The Exponential Distribution (Optional)

Sampling Distributions

What Is a Sampling Distribution? Properties of Sampling Distributions

Unbiasedness and Minimum Variance (Optional)

The Central Limit Theorem

Inferences Based on a Single Sample: Estimation with Confidence Intervals